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Sentrint
Summary
You built the app with Claude, shipped it, and only later discovered your API keys were sitting in plain text inside a public repo — because nobody ran a security scan before you clicked deploy.
Sentrint takes the GitHub URL of an AI-generated app and runs it through a four-category security engine: hardcoded secrets, database access rules, dependency vulnerabilities, and dangerous code paths where user input reaches a command. An AI layer then filters the results, discarding findings the engine flagged but that are not actually exploitable, so you are not chasing noise. What comes back is a score out of 100, every finding written in plain English, and a fix prompt already rewritten for the specific LLM platform that built the app — paste it in, scan again, watch the grade move. The ceiling appears fast: no API access, no CI integration, no self-hosting, and no way to automate scans without a human clicking through the interface each time.
Bottom line: Sentrint fits the developer who vibe-coded an app on a weekend and needs to know whether it is safe to share the link — it breaks down the moment a team wants scans running automatically on every pull request.
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Pros
Sign in to edit- AI-filtered results strip out findings that are not actually exploitable, so you spend time fixing real vulnerabilities instead of chasing false alarms that a raw static analysis tool would dump on you.
- Fix prompts are rewritten for the specific LLM platform that built the app — Claude, Gemini, or any of the 16 supported platforms — so a non-technical builder can paste the output directly back into their coding agent without translating a security finding into an instruction.
- Plain-English explanations of every finding mean a product manager or solo indie developer can read the report and understand what is broken, without needing a security engineer to interpret CVE IDs or stack traces.
- Score-over-time tracking across multiple scans gives you a visible signal that fixes are landing — not just a one-time snapshot, but a trend line that confirms the grade is actually climbing.
Cons
Sign in to edit- There is no API and no CI/CD integration, so every scan requires a human to initiate it manually through the interface — any team that wants scans running automatically on pull requests or blocking a deployment on a failing grade hits this wall immediately and has to move to a tool like Snyk or Semgrep that exposes pipeline hooks.
- The scan covers four fixed categories: secrets, access rules, dependencies, and code paths. Teams whose apps have security concerns outside those categories — authentication logic, rate limiting, business-logic flaws — get no coverage and no signal, with no way to extend the engine.
- No self-hosted option means every repository you scan is processed on Sentrint's infrastructure — teams under data-residency requirements or working with proprietary codebases they cannot send to a third-party service cannot use the tool at all.
About
- Platforms
- Web
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-09-09T03:38:43.605Z
Best For
Who it's for
- Non-technical builders using AI coding agents
- Indie developers shipping vibe-coded apps
- Teams needing plain-English security reports
What it does well
- Scan AI-generated app repositories for security flaws
- Generate platform-specific fix prompts for detected issues
- Track security score trends across multiple scans
Integrations
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Sign Up to ContributeFrequently Asked Questions
- Is Sentrint free?
- Sentrint has a permanent free tier alongside paid upgrades. You can keep using a baseline version indefinitely without paying.
- Is Sentrint open source?
- No — Sentrint is a closed-source tool. Source code is not publicly available.
- What platforms does Sentrint support?
- Sentrint is available on: Web.
Curated lists that include this category
AI coding agents ship code fast and check almost nothing. Sentrint exists for the gap that creates: a one-shot security scanner that reads the repository behind your AI-built app and returns a graded report before a real user — or a real attacker — finds the problems first. The workflow is direct: point Sentrint at the repo, the security engine reads every file across four categories (hardcoded secrets, database access rules, open-source dependency vulnerabilities, and code paths where external input reaches a command), an AI layer removes false positives, and you receive a score out of 100 with a letter grade, plain-English descriptions of each finding, and a fix prompt formatted for whichever of the 16 supported LLM platforms generated your code.
The differentiating detail is the platform-specific fix prompt. Rather than returning a generic patch or a CVE reference, Sentrint rewrites the fix as something you can paste directly back into Claude, Gemini, or any of the other supported platforms. For a non-technical builder who cannot read a diff, that closes the loop — scan, paste, re-scan, grade climbs — without requiring the user to translate a security finding into an instruction their AI coding agent can act on.
Sentrint targets indie builders and non-technical teams who are shipping AI-generated code and have no security review in their process at all. It does not target teams with existing DevSecOps pipelines. There is no API, no CI/CD hook, no self-hosted option, and no way to trigger a scan programmatically — every scan requires a manual session. Teams that need scans on every commit, or that want to gate a deployment on a passing security score, will exhaust what Sentrint offers and move to a tool that exposes an API or integrates with their pipeline. The free tier provides six checks without an account, which the vendor describes as enough to demonstrate how a scan works.